Fuzzy Believer

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Overview

The growing number of publicly available information sources makes it impossible for individuals to keep track of all the various opinions on one topic. The goal of our fuzzy believer project is to extract and analyze statements of opinion from newspaper articles.

Beliefs are modeled using a fuzzy-theoretic approach applied after NLP-based information extraction. A fuzzy believer models a human agent, deciding what statements to believe or reject based on different, configurable strategies.

Resources

Our reported speech tagging components are now available as free/open source software.

Publications

A list of publications is also available.

Project Members

Project supervision:

• Sabine Bergler (CLaC lab)
• René Witte

Project Members:

• Ralf Krestel